ggml: aarch64: Implement SVE F16 kernels for vector functions #15115
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@ggerganov , request you to kindly review the PR and support for merger |
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@ggerganov, @compilade, please review this PR. |
ggerganov
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Same comment as in #15057 (review). We don't even have CI hardware to test these changes, so it's difficult to approve these.
Let's merge after you fix the editor config errors.
walidbr
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…rg#15115) * Added sve implementation for vec_dot_fp16 Kernel * removed white spaces * Added comment * removed white spaces * changed GGML_F16x_VEC_FMA for code consistency * Update vec.h --------- Co-authored-by: vithulep <[email protected]>
Nexesenex
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…ggml-org#15115)" This reverts commit a0c2b20.
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This PR adds SVE kernel support for the f16 (ggml_vec_dot_f16() Kernel) data type to reduce the time required for image encoding during LMM model (llava-v1.6-mistral) inference on ARM architecture.
Major code changes:
In vec.cpp file:
In vec.h file:
In simd-mappings.h:
Performance: Graviton3E
On Graviton3E with different threads, got 5-15% speedup on Image Encoding time for multimodal (LMM) inference.
Model: llava-v1.6-mistral-7b.Q4_K_M
Machine: Graviton3E
Command Used:
Perplexity
I have ran perplexity with the NEON(Original) and SVE (This PR) Implementation.
And below is the summary.
This correction does not appear to have any impact on accuracy.